
"""simple docstring"""



import logging
import os
import sys
from pathlib import Path
from unittest.mock import patch

from parameterized import parameterized
from run_eval import run_generate
from run_eval_search import run_search

from transformers.testing_utils import CaptureStdout, TestCasePlus, slow
from utils import ROUGE_KEYS


logging.basicConfig(level=logging.DEBUG)
a       :						Optional[int]       		=		logging.getLogger()


def 			_UpperCamelCase						(    _A       ,   _A   )     ->	Any:





    """simple docstring"""

    _UpperCAmelCase        = """\n""".join(_A   )
    Path(_A   ).open("""w"""   ).writelines(_A   )


a       :						Any       		=		'''patrickvonplaten/t5-tiny-random'''
a       :						Union[str, Any]       		=		'''sshleifer/bart-tiny-random'''
a       :						Tuple       		=		'''sshleifer/tiny-mbart'''

a       :						Any       		=		logging.StreamHandler(sys.stdout)
logger.addHandler(stream_handler)
logging.disable(logging.CRITICAL)  # remove noisy download output from tracebacks







class 		a_    (			_UpperCAmelCase						):







    def   _snake_case       (      self      :							List[str]  ,       __UpperCamelCase      :							str  )		->Union[str, Any]:






        '''simple docstring'''






        _UpperCAmelCase        = Path(self.get_auto_remove_tmp_dir()  ) / """utest_input.source"""
        _UpperCAmelCase        = input_file_name.parent / """utest_output.txt"""
        assert not output_file_name.exists()
        _UpperCAmelCase        = [""" New York (CNN)When Liana Barrientos was 23 years old, she got married in Westchester County."""]
        _dump_articles(__UpperCamelCase  ,       __UpperCamelCase  )

        _UpperCAmelCase        = str(Path(self.get_auto_remove_tmp_dir()  ) / """scores.json"""  )
        _UpperCAmelCase        = """translation_en_to_de""" if model == T5_TINY else """summarization"""
        _UpperCAmelCase        = f"""
            run_eval_search.py
            {model}
            {input_file_name}
            {output_file_name}
            --score_path {score_path}
            --task {task}
            --num_beams 2
            --length_penalty 2.0
            """.split()

        with patch.object(__UpperCamelCase  ,       """argv"""  ,       __UpperCamelCase  ):
            run_generate()
            assert Path(__UpperCamelCase  ).exists()
            # os.remove(Path(output_file_name))







    def   _snake_case       (      self      :							Optional[int]  )		->Dict:






        '''simple docstring'''






        self.run_eval_tester(__UpperCamelCase  )







    @parameterized.expand([BART_TINY, MBART_TINY]  )
    @slow
    def   _snake_case       (      self      :							List[Any]  ,       __UpperCamelCase      :							List[str]  )		->Optional[int]:






        '''simple docstring'''






        self.run_eval_tester(__UpperCamelCase  )







    @parameterized.expand([T5_TINY, MBART_TINY]  )
    @slow
    def   _snake_case       (      self      :							List[str]  ,       __UpperCamelCase      :							int  )		->Any:






        '''simple docstring'''






        _UpperCAmelCase        = Path(self.get_auto_remove_tmp_dir()  ) / """utest_input.source"""
        _UpperCAmelCase        = input_file_name.parent / """utest_output.txt"""
        assert not output_file_name.exists()

        _UpperCAmelCase        = {
            """en""": ["""Machine learning is great, isn't it?""", """I like to eat bananas""", """Tomorrow is another great day!"""],
            """de""": [
                """Maschinelles Lernen ist großartig, oder?""",
                """Ich esse gerne Bananen""",
                """Morgen ist wieder ein toller Tag!""",
            ],
        }

        _UpperCAmelCase        = Path(self.get_auto_remove_tmp_dir()  )
        _UpperCAmelCase        = str(tmp_dir / """scores.json"""  )
        _UpperCAmelCase        = str(tmp_dir / """val.target"""  )
        _dump_articles(__UpperCamelCase  ,       text["""en"""]  )
        _dump_articles(__UpperCamelCase  ,       text["""de"""]  )
        _UpperCAmelCase        = """translation_en_to_de""" if model == T5_TINY else """summarization"""
        _UpperCAmelCase        = f"""
            run_eval_search.py
            {model}
            {str(__UpperCamelCase  )}
            {str(__UpperCamelCase  )}
            --score_path {score_path}
            --reference_path {reference_path}
            --task {task}
            """.split()
        testargs.extend(["""--search""", """num_beams=1:2 length_penalty=0.9:1.0"""]  )

        with patch.object(__UpperCamelCase  ,       """argv"""  ,       __UpperCamelCase  ):
            with CaptureStdout() as cs:
                run_search()
            _UpperCAmelCase        = [""" num_beams | length_penalty""", model, """Best score args"""]
            _UpperCAmelCase        = ["""Info"""]
            if "translation" in task:
                expected_strings.append("""bleu"""  )
            else:
                expected_strings.extend(__UpperCamelCase  )
            for w in expected_strings:
                assert w in cs.out
            for w in un_expected_strings:
                assert w not in cs.out
            assert Path(__UpperCamelCase  ).exists()
            os.remove(Path(__UpperCamelCase  )  )

"""simple docstring"""



import warnings
from functools import wraps
from typing import Callable


def 			_UpperCamelCase						(    _A   )     ->	Callable:





    """simple docstring"""

    @wraps(_A   )
    def _inner_fn(*_A       ,   **_A   ):
        warnings.warn(
            (F"""'{fn.__name__}' is experimental and might be subject to breaking changes in the future.""")       ,   _A       ,   )
        return fn(*_A       ,   **_A   )

    return _inner_fn